Secure Outsourced Private Set Intersection with Linear Complexity

Debnath, Sumit Kumar; Sakurai, Kouchi; Dey, Kunal; Kundu, Nibedita

doi:10.1109/dsc49826.2021.9346230

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Under the condition of protecting the privacy of the sets of parties, the common method used to measure the spatiotemporal matching level of the two parties is PSI-CA, a variant of PSI [14]. Te PSI-CA protocol allows a party to obtain the cardinality of the intersection of the private sets with another party without revealing information other than the intersection cardinality [15].…”

Section: Related Workmentioning

confidence: 99%

PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles

Jiang,

Yu,

Chen

et al. 2023

Security and Communication Networks

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In recent years, the development of the Internet of Vehicles (IoV) has led to an increase in the demand for data sharing services for the IoV. In the era of big data, safe and convenient data sharing services for IoV are inseparable from the support of reliable data. With the increase in the number of smart cars, how to filter the data provided by vehicles while protecting privacy to improve the quality of data sharing services has attracted the attention of scholars. However, in the existing data sharing scheme for IoV, the vehicles that provide data are selected based on the reputation mechanism or the voting mechanism. Our analysis shows that these two mechanisms lack objectivity and are vulnerable to cooperative attack. Therefore, based on spatiotemporal matching, a new trusted relationship establishment method, this paper proposes an objective and cooperative attack-resistant vehicle selection scheme for data sharing in IoV. Bloom filters and an exponential ElGamal encryption scheme are used to implement private set intersection cardinality (PSI-CA) technology for evaluating spatiotemporal matching level. In this paper, the scheme proposed is of great significance to improve existing vehicle services and improve driving safety.

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Section: Related Workmentioning

confidence: 99%

PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles

Jiang,

Yu,

Chen

et al. 2023

Security and Communication Networks

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“…PSI has wide applications such as social discovery [1][2][3], document-like detection [4], joint learning in neural network models [5], suspect detection [6], privacy-preserving data mining [7], privacy-preserving retrieval systems [8], cloud-based applications [9], and so on. Many high-performance PSI protocols have been proposed recently [10][11][12][13][14][15][16]. Additionally, there are some PSI protocols [10,[17][18][19][20][21] specifically designed for unbalanced scenarios, where the server has a large dataset and the client has a dataset much smaller than the server's size.…”

Section: Introductionmentioning

confidence: 99%

A Practical Multiparty Private Set Intersection Protocol Based on Bloom Filters for Unbalanced Scenarios

Ruan,

Yan,

Zhou

et al. 2023

Applied Sciences

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Multiparty Private Set Intersection (MPSI) is dedicated to finding the intersection of datasets of multiple participants without disclosing any other information. Although many MPSI protocols have been presented, there are still some important practical scenarios that require in-depth consideration such as an unbalanced scenario, where the server’s dataset is much larger than the clients’ datasets, and in cases where the number of participants is large. This paper proposes a practical MPSI protocol for unbalanced scenarios. The protocol uses the Bloom filter, an efficient data structure, and the ElGamal encryption algorithm to reduce the computation of clients and the server; adopts randomization technology to solve the encryption problem of the 0s in the Bloom filter; and introduces the idea of the Shamir threshold secret-sharing scheme to adapt to multiple environments. A formal security proof and three detailed experiments are given. The results of the experiments showed that the new protocol is very suitable for unbalanced scenarios with a large number of participants, and it has a significant improvement in efficiency compared with the typical related protocol (TIFS 2022).

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“…So it has become an important research object to solve the problem of edge-assisted Internet of ings data privacy sharing. PSI protocol [6] refers to the intersection of two participants calculating their private sets. In the edge computing environment, two clients encrypt their respective data sets and outsource them to the edge server.…”

Section: Introductionmentioning

confidence: 99%

Outsourced Mutual Private Set Intersection Protocol for Edge-Assisted IoT

Zhang

Qin

et al. 2021

Security and Communication Networks

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The development of edge computing and Internet of Things technology has brought convenience to our lives, but the sensitive and private data collected are also more vulnerable to attack. Aiming at the data privacy security problem of edge-assisted Internet of Things, an outsourced mutual Private Set Intersection protocol is proposed. The protocol uses the ElGamal threshold encryption algorithm to rerandomize the encrypted elements to ensure all the set elements are calculated in the form of ciphertext. After that, the protocol maps the set elements to the corresponding hash bin under the execution of two hash functions and calculates the intersection in a bin-to-bin manner, reducing the number of comparisons of the set elements. In addition, the introduction of edge servers reduces the computational burden of participating users and achieves the fairness of the protocol. Finally, the IND-CPA security of the protocol is proved, and the performance of the protocol is compared with other relevant schemes. The evaluation results show that this protocol is superior to other related protocols in terms of lower computational overhead.

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Secure Outsourced Private Set Intersection with Linear Complexity

Cited by 4 publications

References 21 publications

PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles

PSI-CA-Based Vehicle Selection Scheme for Data Sharing in Internet of Vehicles

A Practical Multiparty Private Set Intersection Protocol Based on Bloom Filters for Unbalanced Scenarios

Outsourced Mutual Private Set Intersection Protocol for Edge-Assisted IoT

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